Traffic-related Particulate Matter Research Articles

A six-year measurement-based analysis of traffic-related particulate matter pollution in urban areas: the case of Warsaw, Poland (2016-2021)

This study used PM10 and PM2.5 measurements from the State Environmental Monitoring stations in Warsaw and its suburban areas. Analysis of variability characteristics at the traffic and urban background stations was carried out for 2016-2021. A six-year analysis (2016-2021) of air quality in Warsaw, Poland, focusing highlights the persistent impact of transportation on particulate matter concentrations. Comparing a city centre traffic station with urban background locations reveals consistently higher PM10 concentrations at the traffic station throughout the year, with an annual traffic-related increase of 12.6 μg/m³ (32%). PM2.5 concentrations at the traffic station are also consistently about 1.5 μg/m³ (7%) higher. For monthly averages, the highest PM10 concentrations at the traffic station were noted in March, which may be related to the resuspention of sand and salt left over from winter snow removalp rocesses. In the case of PM2.5, the typical annual cycle with maximum concentrations in winter and minimum concentrations in summer was not observed. Diurnal variability patterns show elevated PM10 concentrations at the traffic station from 8:00 a.m. to 10:00 p.m., attributed to the resuspension process. PM2.5 patterns exhibit a smaller amplitude at the traffic station, with nighttime accumulation due to inflow. This study emphasizes the lasting impact of transportation on air quality, providing insights into pollution control strategies in urban areas.

An urban design decision-support framework for distancing walkway pedestrians from traffic-related particulate matter

Human exposure to traffic-related particulate matter (PM) has adverse health effects on individuals. A decision-support framework is proposed to help urban planners and policymakers implement measures to reduce walkway pedestrian exposure to traffic-related PM. The framework consisted of two parts: Part I determined urban walkway rankings based on priority needs for mitigation design solutions. This was achieved by weighting data on air quality monitoring, pedestrian flow, and pedestrian behaviour collected both manually and using handheld devices. Part II assessed the suitability of design solutions for each urban walkway by evaluating (on a three-point scale) the physical applicability, implementation cost, and environmental and social added values of six urban design mitigation solutions (S1–S6). The proposed framework was demonstrated using four urban walkways (W1–W4) in Jeddah, Saudi Arabia. Two data-collection sampling cycles (winter and summer) were conducted in the year 2023. The findings indicated that the framework was successful in ordering the walkways (from highest to lowest priority need): W4, W1, W3, and W2. Additionally, the framework was successful in ordering the mitigation solutions from highest to lowest suitability for W1–W4 (e.g., S2, S3, and S4, in order, were recommended for W3). The proposed framework provides a structured decision-making approach, enabling efficient resource allocation, strategic planning, risk mitigation, transparent decision-making, and optimised impact.

Accumulation of Atmospheric PAHs in White Mustard – Can the Seeds Be Affected?

Traffic-related particulate matter emissions have been considerably reduced due to stringent regulations in Europe. However, emission of diesel-powered vehicles still poses a significant environmental threat, affecting rural ecosystems and agriculture. Several studies have reported that polycyclic aromatic hydrocarbons (PAHs), a group of potentially toxic organic compounds, can accumulate in crops and vegetables. In our study, white mustard (Sinapis alba L.) plants were experimentally treated with an extract of diesel exhaust. PAH concentrations were measured in the different plant compartments (stems, leaves and seeds), bioconcentration factors (BCFs) were also calculated. Significant accumulation was measured in the leaves and seeds, stems showed lower accumulation potential. All plant matrices showed high tendency to accumulate higher molecular weight PAHs, BCF was the highest in the 6-ring group. The fact that considerable accumulation was experienced in the seeds might show the risk of cultivating crops nearby roads highly impacted by traffic-related emissions.

Comprehending particulate matter dynamics in transit-oriented developments: Traffic as a generator and design as a captivator

In Transit-Oriented Development (TOD), the close integration of residential structures with community activities and traffic heightens residents' exposure to traffic-related pollutants. Despite traffic being a primary source of particulate matter (PM), the compact design of TODs, together with the impact of urban heat island (UHI), increases the likelihood of trapping emitted PM from traffic, leading to heightened exposure of TOD residents to PM. Although PM originates from two distinct sources in road traffic, exhaust and non-exhaust emissions (NEE), current legislation addressing traffic-related PM from non-exhaust emissions sources remains limited. This paper focuses on two TOD typologies in Manchester City—Manchester Piccadilly and East Didsbury—to understand the roles of TOD traffic as a PM generator and TOD place design as a PM container and trapper. The investigation aims to establish correlations between street design canyon ratios, vehicular Speed, and PM10/PM2.5, providing design guidance and effective traffic management strategies to control PM emissions within TODs. Through mapping the canyon ratio and utilising the Breezometer API for PM monitoring, the paper revealed elevated PM levels in both TOD areas, exceeding World Health Organization (WHO) recommendations, particularly for PM2.5. Correlation analysis between canyon configuration and PM2.5/PM10 highlighted the importance of considering building heights and avoiding the creation of deep canyons in TOD design to minimise the limited dispersion of PM. Leveraging UK road statistics and the PTV Group API for vehicle speed calculations, the paper studied the average speeds on the TOD roads concerning PM. Contrary to conventional assumption, the correlation analyses have revealed a noteworthy association shift between vehicular speed and PM concentrations. A positive correlation existed between speed increase and PM increases on arterial roads. However, a negative correlation emerged on main, collector, and local streets, indicating that PM levels rise for both PM10 and PM2.5 as Speed decreases. These findings challenge the traditional assumption that higher Speed leads to increased emissions, highlighting the potential impact of NEE on PM concentrations. This paper calls for thorough design considerations and traffic management strategies in TOD, especially in dense areas, considering building height, optimising traffic flow, and enhancing compromised air quality associated with vehicular emissions.

How do taxi drivers expose to fine particulate matter (PM2.5) in a Chinese megacity: a rapid assessment incorporating with satellite-derived information and urban mobility data

BackgroundTaxi drivers in a Chinese megacity are frequently exposed to traffic-related particulate matter (PM2.5) due to their job nature, busy road traffic, and urban density. A robust method to quantify dynamic population exposure to PM2.5 among taxi drivers is important for occupational risk prevention, however, it is limited by data availability.MethodsThis study proposed a rapid assessment of dynamic exposure to PM2.5 among drivers based on satellite-derived information, air quality data from monitoring stations, and GPS-based taxi trajectory data. An empirical study was conducted in Wuhan, China, to examine spatial and temporal variability of dynamic exposure and compare whether drivers’ exposure exceeded the World Health Organization (WHO) and China air quality guideline thresholds. Kernel density estimation was conducted to further explore the relationship between dynamic exposure and taxi drivers’ activities.ResultsThe taxi drivers’ weekday and weekend 24-h PM2.5 exposure was 83.60 μg/m3 and 55.62 μg/m3 respectively, 3.4 and 2.2 times than the WHO’s recommended level of 25 µg/m3. Specifically, drivers with high PM2.5 exposure had a higher average trip distance and smaller activity areas. Although major transportation interchanges/terminals were the common activity hotspots for both taxi drivers with high and low exposure, activity hotspots of drivers with high exposure were mainly located in busy riverside commercial areas within historic and central districts bounded by the “Inner Ring Road”, while hotspots of drivers with low exposure were new commercial areas in the extended urbanized area bounded by the “Third Ring Road”.ConclusionThese findings emphasized the need for air quality management and community planning to mitigate the potential health risks of taxi drivers.

Contributions and limitations of environmental magnetism to characterize traffic-related particulate matter sources

SUMMARY The chronic exposure to particulate matter (PM) pollution causes societal and environmental issues, in particular in urban areas where most citizen are regularly exposed to vehicular traffic. Since almost two decades, environmental magnetic monitoring has demonstrated its efficiency to successfully map relative concentrations of airborne particle deposition on accumulative surfaces. A better understanding of the magnetic results requires discriminating the main traffic-related sources of the observed signal on particle collectors. To meet this objective, we investigated a sample set of exhaust and non-exhaust sources with respect to their magnetic fingerprints inferred from hysteresis loops, first-order reversal curve (FORC) diagrams, temperature dependency of initial susceptibility and unmixing of isothermal remanent magnetization acquisition curves. The source sample set comprises 14 diesel and gasoline exhaust smoke residues, 12 abrasive-fatigue wear test pieces from worn brake-pads, brake powders, worn tire-tread and three resuspension products: asphalt concrete, street dust and Saharan mineral dust deposited by precipitation after long-range eolian transport. Magnetic properties of the source samples were compared to those from various accumulative surfaces exposed to urban traffic (passive collectors, filters of facemasks for cycling, plant leaves and tree barks). We found some fingerprints of exhaust pipes and brake wear products on these collectors. The findings highlight the relevance of environmental magnetism tools to characterize different traffic-related source signals in accumulative surfaces in urban environment.

Particulate matter from car exhaust alters function of human iPSC-derived microglia

BackgroundAir pollution is recognized as an emerging environmental risk factor for neurological diseases. Large-scale epidemiological studies associate traffic-related particulate matter (PM) with impaired cognitive functions and increased incidence of neurodegenerative diseases such as Alzheimer’s disease. Inhaled components of PM may directly invade the brain via the olfactory route, or act through peripheral system responses resulting in inflammation and oxidative stress in the brain. Microglia are the immune cells of the brain implicated in the progression of neurodegenerative diseases. However, it remains unknown how PM affects live human microglia.ResultsHere we show that two different PMs derived from exhausts of cars running on EN590 diesel or compressed natural gas (CNG) alter the function of human microglia-like cells in vitro. We exposed human induced pluripotent stem cell (iPSC)-derived microglia-like cells (iMGLs) to traffic related PMs and explored their functional responses. Lower concentrations of PMs ranging between 10 and 100 µg ml−1 increased microglial survival whereas higher concentrations became toxic over time. Both tested pollutants impaired microglial phagocytosis and increased secretion of a few proinflammatory cytokines with distinct patterns, compared to lipopolysaccharide induced responses. iMGLs showed pollutant dependent responses to production of reactive oxygen species (ROS) with CNG inducing and EN590 reducing ROS production.ConclusionsOur study indicates that traffic-related air pollutants alter the function of human microglia and warrant further studies to determine whether these changes contribute to adverse effects in the brain and on cognition over time. This study demonstrates human iPSC-microglia as a valuable tool to study functional microglial responses to environmental agents.

Development of brake activity measurement method for heavy-duty vehicles

ABSTRACT Tailpipe PM (particulate matter) emissions have been reduced due to decades of tightening regulations, however non-tailpipe PM emissions are not regulated and are expected to become a significant source of traffic-related PM emissions. Previous studies have focused on emission measurement from laboratory and track tests. Their findings suggest brake wear PM emission rates are dependent on brake activity. Therefore, it is important to characterize brake emissions by first understanding the real-world brake activity from many different vehicle vocations and driving conditions. The goal of the current study is to establish a test method and analysis for brake activity measurements of heavy-duty vehicles. In this study, brake fluid pressure and brake pad temperature were measured for a heavy-duty vehicle during chassis and on-road driving tests. The chassis tests consisted of the Central Business District (CBD) cycle representative of a repetitive stop-and-go driving pattern of a bus, and the Urban Dynamometer Driving Schedule (UDDS) cycle representative of urban driving conditions of heavy-duty vehicles. The on-road tests consisted of a local Riverside City route focused on urban roads at low vehicle speeds with frequent braking, while the second route from Riverside City to Victorville focused on highway driving and downhill braking. The brake pad temperature of the triplicate CBD cycle gradually increased linearly with a slope of 2.3°C/min and the temperature per kinetic energy lost during braking increased by 2.3 × 10−5°C/J for the CBD cycle. The UDDS cycles had the largest kinetic energy loss between 3.2 × 103 to 3.0 × 105 J in the histogram. The local Riverside city route brake temperature increased by 2.0°C/min. The kinetic energy loss for the on-road tests were one order of magnitude larger than that of the dynamometer tests due to brake events occurring under higher speeds. Implications: The non-tailpipe source contributions to traffic related particulate matter (PM) emissions have surpassed that of tailpipe emissions. The results of this work provide a measurement method to obtain brake activity information for a heavy-duty vehicle, which is critical estimating emission inventory accurately.

Developing Machine learning models for hyperlocal traffic related particulate matter concentration mapping

Recently, estimating air pollution concentrations and contributions from various sources has become a major research focus. Our research adds to the body of knowledge by developing machine learning (ML) models to avoid intermediate modeling steps using traffic and meteorological data. The ML model's overall performance in predicting air pollution concentrations at receptors outperforms previous methods. Our best model, Convolutional Long Short-Term Memory (ConvLSTM), has a Mean Relative Error (MRE) of 38.9%, which is lower than the 47.5% MRE for the single hidden layer model, the 63.2% MRE for the Convolutional Neural Network model, and the 41.5% MRE for ConvLSTM with time-series data. Memory cells help the ConvLSTM model predict a large number of spatially correlated observations. The novel ML modeling approach has low data requirements and is computationally efficient, which makes it promising for future transportation planning, epidemiology, and environmental justice assessments.

Impacts of viaduct and geometry configurations on the distribution of traffic-related particulate matter in urban street canyon

Viaduct is a ubiquitous transportation infrastructure in the congested megacities worldwide to improve the accessibility and capacity of urban transportation network. However, there is a lack of understanding of the impacts of the interplay between viaduct-ground emissions and viaduct-canyon configurations on the particle distribution in urban street canyon. To fill the research gap, we conducted vertical measurements of particle number concentrations (PNCs) at different heights of “street canyon along a viaduct” to reveal effect of viaduct on the vertical distribution of PNCs in street canyon. Observation results indicated that the vertical profiles of PNCs exhibited bimodal distribution patterns, which were more significant for coarse particles than fine particles. The one peak appeared at ground level and the other at the viaduct height, indicating the impacts of “double” emission sources (i.e., the emissions on the ground and viaduct) and the hindrance of viaduct to particle diffusion. We further modelled the role of viaduct in street canyon through Computational Fluid Dynamics (CFD) simulations to reveal the vertical distribution of particles under different viaduct-canyon configurations and discern the contributions of viaduct and ground emissions to the particle distribution. Simulation results showed that viaduct changed airflow field and turbulence structure and elevated particle concentrations in street canyon while the optimized viaduct-canyon configurations including higher viaduct height (12 > 10 > 8 m), smaller aspect ratio (0.5 > 0.67 > 1), and shorter centerline distance (0 > 1 > 2 m) between canyon and viaduct could bring better dispersion conditions and lower particle concentrations. Additionally, ground emissions contributed more to the vertical distribution of particles on the leeward side of street canyon than viaduct emissions while the windward side displayed the opposite characteristics to the leeward side. These findings revealed the general patterns of particle diffusion in viaduct-canyon configurations and provided implications into viaduct design and traffic management to alleviate local particulate pollution.

Particulate matter fingerprints in biofuel impacted tunnels in South America's largest metropolitan area

This study characterized the chemical composition of particulate matter (PM) from light- (LDV) and heavy-duty (HDV) vehicles based on two traffic tunnel samplings carried out in the megacity of São Paulo (Brazil), which has >7 million vehicles and intense biofuel use. The samples were collected with high-volume samplers and analyzed using chemical characterization techniques (ion and gas chromatography, thermal-optical analysis, and inductively coupled plasma mass spectroscopy). Chemical source profiles (%) were calculated based on the measurements performed inside and outside the tunnels. Identifying a high abundance of Fe and Cu for traffic-related PM in the LDV-impacted tunnel was possible, linked with the emission of vehicles powered by ethanol and gasohol (gasoline and ethanol blend). We calculated diagnostic ratios (e.g., EC/Cu, Fe/Cu, pyrene/benzo[a]pyrene, pyrene/benzo[b]fluoranthene, and fluoranthene/benzo[b]fluoranthene) characteristic of fuel exhausts (diesel/biodiesel and ethanol/gasohol), allowing their use in the assessment of the temporal variation of the fuel type used in urban sites. Element diagnostic ratios (Cu/Sb and Fe/Cu) pointed to the predominance of LDVs exhaust-related copper and can differentiate LDVs exhaust from brake wear emissions. The carbonaceous fraction EC3 was suggested as an HDV emission tracer. A higher total polycyclic aromatic hydrocarbons (PAHs) fraction of traffic-related PM2.5 was observed in the HDV-impacted tunnel, with a predominance of diesel-related pyrene and fluoranthene, as well as higher oxy-PAHs (e.g., 9,10-anthraquinone, associated with biodiesel blends) abundances. However, carcinogenic species presented higher abundances for the LDV-impacted tunnel (e.g., benzo[a]pyrene). These findings highlighted the impact of biofuels on the characteristic ratios of chemical species and pointed to possible markers for LDVs and HDVs exhausts.

Particulate matter exposure at urban traffic intersection during haze episodes: A case study in Changsha.

Urban intersection has been identified as a major contributor to the total personal exposure and short-term high exposure of particulate matter (PM) in modern cities. The main aim of this study was to get a better understanding of the determinants of traffic-related PM temporal variations and personal exposure to PMs at a viaduct-covered intersection controlled by traffic signals during the winter haze episodes. A two-day field sampling campaign was conducted with a portable device during evening rush hour and measured the PMs in the 0.3-10 μm size range both on the surface crosswalk and underground passage. PM variations and related cumulative respiratory deposition dose (RDD) along two routes with six road crossing scenarios were estimated on a severe pollution day and a typical day for both adults and children, respectively. The PM concentration on the severe pollution day ranged 59.2-67.9 μg/m3 for PM1, 163.8-257.0 μg/m3 for PM2, and 258.2-469.1 μg/m3 for PM10, respectively, as compared to 47.9-57.9 μg/m3for PM1, 112.7-199.8 μg/m3 for PM2, and 151.0-301.0 μg/m3 for PM10 on the typical day, respectively. The variability could be explained largely by the built-up environment, traffic component, signal setting, and ventilation condition. Our data suggest that an appropriate setting of the traffic signal would help reduce the personal exposure dose on the surface crosswalk at urban intersections and the ventilation condition had a significant influence on local PM distributions inside the underground passage. Results here provide possible suggestions for the future design of a walkable city.

Field investigation for ambient wind speed and direction effects exposure of cyclists to PM2.5 and PM10 in urban street environments

In China, an increasing number of cyclists commute on urban streets. Cyclists are usually exposed to high traffic-related particulate matter (PM) concentrations. The distribution of cycling exposure concentrations may be affected by meteorological conditions under different street configurations. To investigate these impacts, we collected concentrations of PM 2.5 and PM 10 at the breathing height of cyclists and meteorological data in two differently oriented streets and an open road in Fuzhou. Relative exposure concentrations (RECs) were determined by subtracting the background concentration and monitoring intervals were determined with the minimisation of the coefficient variation of traffic to identify the impacts of meteorology (e.g., wind speed and wind direction) on REC distribution. Wind speed had the most significant impact on REC and explained 26–63% of the variation in REC. Higher RECs (>6 μg/m 3 ) were mainly distributed at lower wind speeds (<2 m/s), while lower RECs (<3 μg/m 3 ) were dominant when the wind speed exceeded 4 m/s. Temperature and relative humidity were not significantly correlated with the REC. Parallel winds can improve the dispersion of particles. In the up-wind condition, RECs on the leeward side were 2 μg/m 3 higher than those on the windward side because of the accumulation of particles caused by the vortex effect, especially in the west-east streets with residential roadside buildings with strip pattern features. More building gaps on both sides of the streets could weaken the vortex effect, and RECs on the leeward side decreased faster with increasing wind speed. These results can be used to propose strategies for reducing cycling exposure. • Relative exposure concentration (REC) improved the identification of meteorological factors. • Wind speed can explain 26–63% of the variation in cycling REC. • Parallel wind can better benefit the dispersion of particles. • Buildings with strip pattern features can increase REC on the leeward side. • More gaps between buildings can benefit the dispersion of pollutants in urban streets.

Impacts of traffic-related particulate matter pollution on semen quality: A retrospective cohort study relying on the random forest model in a megacity of South China

BackgroundEmerging evidence shows the detrimental impacts of particulate matter (PM) on poor semen quality. High-resolution estimates of PM concentrations are conducive to evaluating accurate associations between traffic-related PM exposure and semen quality. MethodsIn this study, we firstly developed a random forest model incorporating meteorological factors, land-use information, traffic-related variables, and other spatiotemporal predictors to estimate daily traffic-related PM concentrations, including PM2.5, PM10, and PM1. Then we enrolled 1310 semen donors corresponding to 4912 semen samples during the study period from January 1, 2019, and December 31, 2019 in Guangzhou city, China. Linear mixed models were employed to associate individual exposures to traffic-related PM during the entire (0–90 lag days) and key periods (0–37 and 34–77 lag days) with semen quality parameters, including sperm concentration, sperm count, progressive motility and total motility. ResultsThe results showed that decreased sperm concentration was associated with PM10 exposures (β: -0.21, 95 % CI: −0.35, −0.07), sperm count was inversely related to both PM2.5 (β: -0.19, 95 % CI: −0.35, −0.02) and PM10 (β: -0.19, 95 % CI: −0.33, −0.05) during the 0–90 days lag exposure window. Besides, PM2.5 and PM10 might diminish sperm concentration by mainly affecting the late phase of sperm development (0–37 lag days). Stratified analyses suggested that PBF and drinking seemed to modify the associations between PM exposure and sperm motility. We did not observe any significant associations of PM1 exposures with semen parameters. ConclusionOur results indicate that exposure to traffic-related PM2.5 and PM10 pollution throughout spermatogenesis may adversely affect semen quality, especially sperm concentration and count. The findings provided more evidence for the negative associations between traffic-related PM exposure and semen quality, highlighting the necessity to reduce ambient air pollution through environmental policy.

Exposure Assessment of Traffic-Related Air Pollution Based on CFD and BP Neural Network and Artificial Intelligence Prediction of Optimal Route in an Urban Area

Due to rapid global economic development, the number of motor vehicles has increased sharply, causing significant traffic pollution and posing a threat to people’s health. People’s exposure to traffic-related particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) primarily occurs during commuting. Many studies have used exposure risk assessment models to assess the possible adverse effects of PM2.5, but few have used them to plan low-risk pathways for commuters. This study simulated the pollutant concentration distribution in an idealized urban area in different scenarios. We then used a back propagation (BP) neural network to predict the pollutant concentration. The commuter respiratory deposition dose was calculated based on the BP prediction results, and the respiratory deposition dose was converted into obstacles on the commuting map. Finally, the rapidly exploring random tree star (RRT*) algorithm was used to plan low-risk paths for commuters. The results indicate that pollutants discharged by cars and tree planting can significantly affect the pollutant concentration. A 30.25 μg/m3 increase in the pollutant concentration discharged by cars resulted in a 7~13 μg/m3 increase in the traffic-related air pollution concentration on sidewalks. Combining a computational fluid dynamics simulation, a BP neural network model, and the RRT* algorithm provides a system to plan low-risk paths for commuters. This work proposes artificial-intelligence-based models for calculating the exposure risk to traffic-related pollutants (PM2.5) and choosing a low-risk commuting path to ensure healthy travel.

Assessment of plant species suitability in green walls based on API, heavy metal accumulation, and particulate matter capture capacity.

One of the most pressing issues confronting the civilized and modern world is air pollution. Particulate matter (PM) is a well-known pollutant that contributes significantly to urban air pollution and has numerous short- and long-term adverse effects on human health. One method of reducing air pollution is to create green spaces, mainly green walls, as a short-term solution. The current study investigated the ability of nine plant species to reduce traffic-related PM using a green wall system installed along a busy road in Mashhad, Iran. The main aims were (1) estimate the tolerance level of plant species on green walls to air pollution using the air pollution tolerance index (APTI); (2) assess the PM capture on the leaves of green wall species using scanning electron microscopy (SEM), energy dispersive X-ray (EDX) analysis, and accumulation of heavy metals using inductively coupled plasma (ICP); (3) select the most tolerance species for reducing air pollution using anticipated performance index (API). The plants' APTI values ranged from 5 to 12. The highest APTI value was found in Carpobrotus edulis and Rosmarinus officinalis, while Kochia prostrata had the lowest. Among the APTI constituents, leaf water content (R2 = 0.29) and ascorbic acid (R2 = 0.33) had a positive effect on APTI. According to SEM analysis, many PMs were adsorbed on the adaxial and abaxial leaf surfaces, as well as near the stomata of Lavandula angustifolia, C. edulis, Vinca minor, and Hylotelephium sp. Based on EDX analysis, carbon and oxygen formed the highest amount (more than 60%) of metals detected in the elemental composition of PM deposited on the leaves of all species. The Sedum reflexum had the highest Cr, Fe, Pb, and As accumulation. The concentrations of all heavy metals studied in green wall plants were higher than in the control sample. Furthermore, the C. edulis is the best plant for planting in industrial, urban areas of the city based on APTI, biological, economic, and social characteristics. It concludes that green walls composed primarily of plants with small leaves can significantly adsorb PM and accumulation of heavy metal.

Quantifying factors affecting contributions of roadway exhaust and non-exhaust emissions to ambient PM10–2.5 and PM2.5–0.2 particles

Traffic-related particulate matter (PM) plays an important role in urban air pollution. However, sources of urban pollution are difficult to distinguish. This study utilises a mobile particle concentrator platform and statistical tools to investigate factors affecting roadway ambient coarse particle (PM10–2.5) and fine particle (PM2.5–0.2) concentrations in greater Boston, USA. Positive matrix factorization (PMF) identified six PM10–2.5 sources (exhaust, road salt, brake wear, regional pollution, road dust resuspension and tyre-road abrasion) and seven fine particle sources. The seven PM2.5–0.2 sources include the six PM10–2.5 sources and a source rich in Cr and Ni. Non- exhaust traffic-related sources together accounted for 65.6% and 29.1% of the PM10–2.5 and PM2.5–0.2 mass, respectively. While the respective contributions of exhaust sources were 10.4% and 20.7%. The biggest non-exhaust contributor in the PM10–2.5 was road dust resuspension, accounting for 29.6%, while for the PM2.5–0.2, the biggest non-exhaust source was road-tyre abrasion, accounting for 12.3%. We used stepwise general additive models (sGAMs) and found statistically significant (p < 0.05) effects of temperature, number of vehicles and rush hour periods on exhaust, brake wear, road dust resuspension and road-tyre abrasion with relative importance between 19.1 and 62.2%, 12.5–42.1% and 4.4–42.2% of the sGAM model's explained variability. Speed limit and road type were also important factors for exhaust, road-tyre and brake wear sources. Meteorological variables of wind speed and relative humidity were significantly associated with both coarse and fine road dust resuspension and had a combined relative importance of 38% and 48%. The quantifying results of the factors that influence traffic-related sources can offer key insights to policies aiming to improve near-road air quality.

Exposure to source-specific air pollution and risk for type 2 diabetes: a nationwide study covering Denmark.

Only few epidemiological studies have investigated whether chronic exposure to air pollution from different sources have different impacts on risk of diabetes. We aimed to investigate associations between air pollution from traffic versus non-traffic sources and risk of type 2 diabetes in the Danish population. We estimated long-term exposure to traffic and non-traffic contributions of particulate matter with a diameter <2.5 µg (PM2.5), elemental carbon (EC), ultrafine particles (UFP) and nitrogen dioxide (NO2) for all persons living in Denmark for the period 2005-17. In total, 2.6 million persons aged >35 years were included, of whom 148 020 developed type 2 diabetes during follow-up. We applied Cox proportional hazards models for analyses, using 5-year time-weighted running means of air pollution and adjustment for individual- and area-level demographic and socioeconomic covariates. We found that 5-year exposure to all particle measures (PM2.5, UFP and EC) and NO2 were associated with higher type 2 diabetes risk. We observed that for UFP, EC and potentially PM2.5, the pollution originating from traffic was associated with higher risks than the non-traffic contributions, whereas for NO2 similar hazard ratios (HR) were observed. For example, in two-source models, hazard ratios (HRs) per interquartile change in traffic UFP, EC and PM2.5 were 1.025, 1.045 and 1.036, respectively, whereas for non-traffic UFP, EC and PM2.5, the HRs were 1.013, 1.018 and 1.001, respectively. Our finding of stronger associations with particulate matter from traffic compared with non-traffic sources implies that prevention strategies should focus on limiting traffic-related particulate matter air pollution.

Not Only Trees Matter—Traffic-Related PM Accumulation by Vegetation of Urban Forests

In terms of the process of air purification, a lot of attention has been devoted to trees and shrubs. Little attention has been paid to herbaceous vegetation from the lower forest layers. Urban forests are often located on the outskirts of cities and surround exit roads where there is heavy traffic, generating particulate matter (PM) pollution. The aim of this study was to investigate the spread of PM from the road traffic in the air and to investigate how individual layers of urban forests accumulate PM. We conducted comparative analyses of PM accumulation on plants in five zones away from the road, into the forest, in the air, and in four vegetation layers: mosses, herbaceous plants, shrubs and trees. The results show that all forest layers accumulate PM. We show that PM is very efficiently accumulated by herbaceous plants growing along roadsides, and that the PM that was not deposited on herbaceous plants was accumulated by trees and shrubs. With increasing distance from the road into the forest, the PM content on herbaceous plants decreased and the accumulation on trees and shrubs increased. We estimated that PM concentration in the air dropped significantly in the front line of the trees, but it was still detectable up to 50 m into the forest. The results presented herein show that meadow vegetation and urban forests play a very important role in air purification. Our results provide a better understanding of the complexity of urban forest interactions and provide the basis for better planning of urban greenery.

Assessment of personal exposure to PM for multiple transportation modes

• PM concentrations and inhalation doses in Guangzhou presented the following trend: shared bikes > buses > cars > subways. • The counts of particle size range of 0.25–0.5 µm were highest in all travel modes. • Travel by “cars CW” (i.e., with closed windows) effectively prevented PM infiltration from outside air. • PM concentrations on weekends with peaks usually observed in the morning, were higher than those on weekdays. Travelers are severely exposed to traffic-related particulate matter (PM). To assess the personal exposure to PM for multiple transportation modes, we conducted a study on particle concentrations, size fractions, and inhalation doses in Guangzhou, China. PM concentrations and inhalation doses showed the following trend: shared bikes > buses > cars > subways. PM 0.25-1 concentrations in subway accounted for 56%–63% of all size fractions, while PM 2.5-10 dominated PM 0.25-2.5 in other modes. The highest particle counts were observed in the size range of 0.25–0.5 µm. PM concentrations on weekends were higher than those on weekdays. Peak concentrations were usually recorded in the morning on weekends but in the evening during weekdays. Females had higher exposure risks than males for the same distance covered using shared bikes due to longer travel duration. These results can provide theoretical guides for travelers to reduce personal exposure and health risks associated with PM.